Daniel Ledwoń

Research and teaching assistant

Silesian University of Technology

Poland

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About

Daniel Ledwoń is a Research and Teaching Assistant at Silesian University of Technology in Poland. His research focuses on the application of quantitative EEG analysis, machine learning in cognitive impairment related to Parkinson’s disease, and the assessment of retinal morphology in relation to age-related macular degeneration. He has contributed to various studies concerning physiological responses during exercises and advancements in anti-VEGF therapy for neovascular age-related macular degeneration.

Articles (10)

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2025

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2025

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2025

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2024

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2024

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2024

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2024

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2024

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2024

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2024

Collaborators (6)

Andrzej Waldemar Mitas

Silesian University of Technology

POLAND

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Anna Wąsowska

Lecturer

Polish-Japanese Academy of Information Technology

POLAND

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Sławomir Teper

Medical University of Silesia

POLAND

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Patrycja Romaniszyn-Kania

Silesian University of Technology

POLAND

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Julia Węgrzynek-Gallina

Medical University of Silesia

POLAND

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Monika Bugdol

Silesian University of Technology

POLAND

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Daniel Ledwoń

Research Interests

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Articles (10)

Application of quantitative EEG analysis in machine learning research on cognitive impairment in Parkinson’s disease: A systematic review

Twelve-Month Outcomes of Anti-VEGF Therapy for nAMD with Brolucizumab, Aflibercept, and Ranibizumab in the Polish National Registry: A Multicenter Database Study

Assessment of spontaneous movements of newborns on second or third day of life using computer-aided video analysis

Fundus Image Deep Learning Study to Explore the Association of Retinal Morphology with Age-Related Macular Degeneration Polygenic Risk Score

Flow and Physiological Response Assessment during Exercise Using Metrorhythmic Stimuli

A deep learning approach to explore the association of age‐related macular degeneration polygenic risk score with retinal optical coherence tomography: A preliminary study

Association of Genetic Risk for Age-Related Macular Degeneration with Morphological Features of the Retinal Microvascular Network

Quantitative EEG Spectral and Connectivity Analysis for Cognitive Decline in Amnestic Mild Cognitive Impairment

Quantitative EEG Spectral and Connectivity Analysis for Cognitive Decline in Amnestic Mild Cognitive Impairment

Evaluation of physiological response and synchronisation errors during synchronous and pseudosynchronous stimulation trials

Collaborators (6)

Andrzej Waldemar Mitas

Anna Wąsowska

Sławomir Teper

Patrycja Romaniszyn-Kania

Julia Węgrzynek-Gallina

Monika Bugdol

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